Infrared (IR) imaging systems have sensor and optical limitations that result in degraded imagery. Apart from imperfect optics and the finite detector size being responsible for introducing blurring and aliasing, the detector fixed-pattern noise also adds a significant layer of degradation in the collected imagery. Here, we propose a single-shot super-resolution method that compensates for the nonuniformity noise of long-wave IR imaging systems. The strategy combines wavefront modulation and a reconstruction methodology based on total variation and nonlocal means regularizers to recover high-spatial frequencies while reducing noise. In simulations and experiments, we demonstrate a clear improvement of up to 16× in image resolution while significantly decreasing the fixed-pattern noise in the reconstructed images.